A Persistent Force: Violence in Maurice Gee’s Historical Novels for Children
Bibliographic record
Abstract
Since the publication of his first novel, The Big Season, in 1962, Maurice Gee’s fiction for adults has been noted for its preoccupation with violence. But can we say the same of his fiction for children? And if so, how might that predisposition be reconciled for young readers? Using a predominantly literary-historical reading of Gee’s fiction for children published between 1986 and 1999, this thesis attempts to answer these questions. Chapter 1 establishes the impact of violence on Gee’s early years and its likely influence on his writing. Chapters 2-4 then consider the presence of violence in Gee’s five historical novels for children. Chapter 2 focuses on the wartime novels, The Fire-Raiser and The Champion, and their respective depictions of war and racism, while chapter 3 explores individual, family and social violence as “expanding scenes of violence” (Heim 25) in The Fat Man. The fourth and final chapter discusses the two post-war novels, Orchard Street and Hostel Girl, where social violence runs as an undercurrent of everyday life. The thesis finds that violence – in different forms and at different intensities – persists across the novels and that Gee tempers its presence appropriately for his young readers. Violence, Gee seems to be saying, is part of the mixed nature of the human condition and this knowledge should not be denied children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".